Pieter Jelle Visser

This study maps quantitative trait loci for CSF metabolites and identifies associations with brain traits, revealing potential neurobiological pathways.

The paper develops a multivariate methylation risk score using blood DNA methylation data to predict dementia risk and cognitive impairment in Alzheimer's and Parkinson's disease cohorts.

The paper performs a GWAS on PSP in the Iberian population, replicates known risk variants, and identifies a novel locus in NFASC/CNTN2 associated with oligodendrocyte and myelination processes.

The paper identifies high-priority missense variants in SORL1 associated with increased Alzheimer's Disease risk and earlier onset, suggesting clinical counseling considerations for carriers.

The paper identifies rare damaging variants in ATP8B4 and ABCA1 as novel risk factors for Alzheimer's Disease using exome sequencing data from 32,558 individuals.

This study performs GWAS on quantitative AD biomarkers and cognitive traits, identifying new loci associated with memory performance and cognitive decline.

The paper conducts GWAS on CSF Alzheimer's disease biomarkers, identifying genetic associations with NF-L, YKL-40, and Ng levels.

The paper conducts a genome-wide association study (GWAS) on Alzheimer’s disease CSF biomarkers in the EMIF-AD dataset, identifying novel genetic signals and confirming existing associations.

The DPUK Data Portal provides secure access to cohort data for dementia research, supporting multi-modal analyses and collaborations across multiple institutions.

This study estimates heritability and genetic contributions to metabolite levels using genome-wide data and twin-family cohorts, revealing class-specific genetic influences.

This study shows that serum from MCI patients predicts AD conversion up to 3.5 years before diagnosis by altering hippocampal progenitor cell behavior.

This study uses Bayesian logistic regression to assess if genetic risk factors predict amyloid burden in non-demented individuals, finding that known factors like age and APOE are more predictive than polygenic risk scores.